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    <title>10小时入门大数据</title>
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        <h3>
            第1章 大数据概述
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                    1-1 导学 (10:37) </a>


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                    1-2 章节安排_ (00:43) </a>


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                    1-3 OOTB镜像文件和虚拟机的使用 (04:33) </a>


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                    1-4 说两则故事说起 (03:58) </a>


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                    1-5 大数据与生活息息相关 (01:25) </a>


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                    1-6 大数据基本概念 (05:52) </a>


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                    1-7 大数据带来的挑战 (05:25) </a>


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                    1-8 如何应对大数据带来的挑战 (03:05) </a>


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                    1-9 -如何学好大数据 (02:55) </a>


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            第2章 初识Hadoop
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                    2-1 章节安排 (01:46) </a>


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                    2-2 Hadoop概述 (07:26) </a>


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                    2-3 2.03-Hadoop核心组件之HDFS (07:27) </a>


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                    2-4 2.04-Hadoop核心组件之YARN (04:05) </a>


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                    2-5 2.05-Hadoop核心组件之MapReduce (06:23) </a>


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                    2-6 2.06-Hadoop优势 (02:03) </a>


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                    2-7 2.07-Hadoop发展史 (07:28) </a>


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                    2-8 2.08-Hadoop生态系统 (13:25) </a>


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                    2-9 2.09-Hadoop常用发行版及选型 (06:06) </a>


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                    2-10 2.10-Hadoop应用案例 (03:45) </a>


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            第3章 分布式文件系统HDFS
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                    3-1 -课程目录- (01:24) </a>


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                    3-2 -普通分布式文件系统的设计思路 (07:56) </a>


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                    3-3 HDFS概述及设计目标 (08:00) </a>


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                    3-4 HDFS架构 (09:53) </a>


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                    3-5 HDFS副本机制 (06:27) </a>


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                    3-6 HDFS副本存放策略 (02:15) </a>


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                    3-7 JDK安装&amp;ssh安装&amp;ssh免密码登陆配置 (09:42) </a>


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                    3-8 HDFS伪分布式环境搭建 (17:16) </a>


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                    3-9 HDFS shell操作 (14:20) </a>


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                    3-10 Java操作HDFS开发环境搭建 (07:39) </a>


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                    3-11 Java API操作HDFS文件系统 (31:58) </a>


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                    3-12 HDFS写数据流程 (11:19) </a>


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                    3-13 HDFS读数据流程 (03:34) </a>


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                    3-14 HDFS文件系统的优缺点 (01:58) </a>


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            第4章 分布式资源调度YARN
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                    4-1 -课程目录 (01:23) </a>


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                    4-2 -YARN产生背景 (12:37) </a>


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                    4-3 -YARN架构 (13:18) </a>


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                    4-4 -YARN执行流程 (04:20) </a>


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                    4-5 -YARN环境搭建 (08:22) </a>


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                    4-6 -初识提交PI的MapReduce作业到YARN上执行 (06:08) </a>


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            第5章 分布式计算框架MapReduce
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                    5-1 -课程目录 (00:50) </a>


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                    5-2 -MapReduce概述 (07:34) </a>


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                    5-3 -从WordCount案例说起MapReduce编程模型 (11:52) </a>


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                    5-4 -MapReduce执行流程 (16:39) </a>


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                    5-5 -MapReduce核心概念 (05:09) </a>


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                    5-6 -MapReduce1.x架构 (07:12) </a>


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                    5-7 -MapReduce2.x架构 (02:31) </a>


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                    5-8 -Java版本wordcount功能实现 (23:38) </a>


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                    5-9 -Java版本wordcount功能重构 (07:28) </a>


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                    5-10 -Combiner应用程序开发 (06:02) </a>


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                    5-11 -Partitioner应用程序开发 (08:31) </a>


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                    5-12 JobHistory使用 (08:38) </a>


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            第6章 Hadoop项目实战
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                    6-1 -课程目录-- (01:05) </a>


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                    6-2 用户行为日志概述 (13:19) </a>


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                    6-3 离线数据处理架构 (10:54) </a>


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                    6-4 项目需求 (02:40) </a>


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                    6-5 功能实现之UserAgent解析类测试 (08:32) </a>


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                    6-6 功能实现之单机本地完成需求统计 (16:06) </a>


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                    6-7 使用MapReduce完成需求统计 (13:09) </a>


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                    6-8 功能扩展思路 (01:14) </a>


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            第7章 Hadoop分布式集群搭建
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                    7-1 -课程目录 (01:03) </a>


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                    7-2 -分布式环境搭建之环境介绍 (04:40) </a>


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                    7-3 -分布式环境搭建前置配置之ssh免密码登陆 (05:06) </a>


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                    7-4 -分布式环境搭建前置配置之JDK安装 (02:10) </a>


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                    7-5 -分布式环境搭建集群搭建之Hadoop配置及分发 (12:20) </a>


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                    7-6 -分布式环境搭建Hadoop格式化及启停 (06:25) </a>


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                    7-7 -分布式环境HDFS及YARN的使用 (02:21) </a>


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                    7-8 -将Hadoop项目运行在Hadoop集群之上 (05:22) </a>


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            第8章 Hadoop集成Spring的使用
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                    8-1 -课程目录 (01:13) </a>


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                    8-2 -Spring Hadoop概述 (04:12) </a>


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                    8-3 -Spring Hadoop开发环境搭建及访问HDFS文件系统 (15:10) </a>


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                    8-4 -Spring Hadoop配置文件详解 (03:52) </a>


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                    8-5 -Spring Boot访问HDFS文件系统 (06:10) </a>


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                    8-6 -Spring Hadoop其他 (02:09) </a>


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            第9章 前沿技术拓展: Spark/Flink/Beam
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                    9-1 -课程目录 (01:57) </a>


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                    9-2 -吐槽MapReduce (05:03) </a>


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                    9-3 -Spark特点 (10:49) </a>


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                    9-4 -Spark与Hadoop深入对比 (09:02) </a>


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                    9-5 -Spark开发语言及运行模式介绍 (03:15) </a>


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                    9-6 -Scala&amp;Maven安装 (02:29) </a>


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                    9-7 -Spark环境搭建及wordcount案例实现 (12:11) </a>


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                    9-8 -Flink概述 (08:31) </a>


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                    9-9 -使用Flink完成wordcount统计 (07:40) </a>


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                    9-10 -Beam概述 (03:29) </a>


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                    9-11 -将WordCount的Beam程序以多种不同Runner运行 (10:59) </a>


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                    9-12 -课程目录 (01:57) </a>


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        <h3>
            第10章 Hadoop3.x新特性
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                    10-1 -课程目录 (01:11) </a>


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                    10-2 -Hadoop3.x概述 (03:22) </a>


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                    10-3 -Hadoop3.x新特性之Common改进 (06:19) </a>


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                    10-4 -Hadoop3.x新特性之HDFS改进 (10:06) </a>


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                    10-5 -Hadoop3.x新特性之YARN改进 (04:42) </a>


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                    10-6 -Hadoop3.x新特性之MapReduce改进 (02:12) </a>


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                    10-7 -Hadoop3.x新特性之其他 (02:59) </a>


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